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A Holistic Approach to Measuring Information Quality
January 2007
Alan Snow

The path taken by data on its long and sometimes complex transformation into Business Information is full of potential pitfalls. Decision-makers (that's most of us!) use information to know "what's going on" in various parts of the business, and to measure progress or performance against set goals (such as may be expressed in KPIs).

Recent surveys 2 confirm that the majority of companies acknowledge the role that data quality ('DQ') and information quality ('IQ') play in producing reliable Business Intelligence, but fewer than 1 in 20 companies have developed an information quality management ('IQM') strategy. Such a strategy helps ensure that the business value of information is maximised, and the risk of using information of low or unknown quality is reduced to the minimum. The use of unreliable information to evaluate progress and performance is — at the least — risky, and at worst downright dangerous.